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Speaker 2: Erness What's Up?

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Speaker 1: You ever walk into a small business and everything just

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Speaker 1: pushing your vision forward.

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Speaker 3: In Nvidia. Few things that stuck out to me.

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Speaker 4: Jensen was very very adamant a few things, but one

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Speaker 4: thing in particular was physical AI. Yes and yes in

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Speaker 4: the in the marketplace. So you asked, what's physical robot

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Speaker 4: what's physical AI robotics? He brought the robot on stage

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Speaker 4: with him. In the marketplace, there was tons of robots.

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Speaker 4: We put it on Instagram, as far as the dog,

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Speaker 4: the the guy that was doing shout out to Alex

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Speaker 4: good energy on the check in, the guy that was

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Speaker 4: picking up the stuff in the factories. So there was

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Speaker 4: two things that Jensen was really big on robotics, and

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Speaker 4: the other key takeaway that I got was the rational

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Speaker 4: aspect of artificial intelligence.

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Speaker 3: That's the new wave. I forget the exactly agent AI.

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Speaker 4: So, all right, like artificial intelligence as we know it today, right,

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Speaker 4: let's take chat GBT. You asked it questions and it

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Speaker 4: gives you answers, right, But if you ask it like

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Speaker 4: two complex questions, it'll say I can't answer that question,

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Speaker 4: or that's debatable, or it kind of stares away from asking.

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Speaker 4: Like if you say, okay, what's the best religion in

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Speaker 4: the world, they'll say, like, that's a debatable which it

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Speaker 4: is debatable, right, But if I ask a person that

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Speaker 4: based on their personal beliefs, based on their rational thinking,

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Speaker 4: based on their upbringing, they'll tell me it's Christianity.

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Speaker 3: They'll tell me it's Islam, its Buddhism.

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Speaker 4: That's their personal opinions, and that's how conversations happen with

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Speaker 4: real people.

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Speaker 3: Right.

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Speaker 4: But AI doesn't work like that right now. But the

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Speaker 4: next iteration of AI is a rational thought process where

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Speaker 4: it's actually thinking in real time, it's rationalizing situations and

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Speaker 4: its algorithm and it's giving you answers based off of

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Speaker 4: not only it's intelligence, but also it's rational mind. That's

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Speaker 4: what's kind of separating humans from AI right now, because

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Speaker 4: they already have intelligence, but they don't have the emotional intelligence,

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Speaker 4: the rational the how to talk. That's the next iteration

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Speaker 4: of AIS. So if you think about it, like, what

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Speaker 4: that's going to do is lower the value of education

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Speaker 4: because like let's say, like right now, lawyers get paid

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Speaker 4: from a scarcity of knowledge that only a select few

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Speaker 4: people in the world have. Like, if you have a

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Speaker 4: law degree, you're in a select few group of people

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Speaker 4: in the total sum of the world, right, And that

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Speaker 4: knowledge that you've acquired over eight years and then working,

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Speaker 4: that's made your education scarce, and that's major knowledge scarce,

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Speaker 4: which makes.

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Speaker 3: Your value high.

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Speaker 2: Absolutely.

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Speaker 4: Now if everybody has that same knowledge and that same

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Speaker 4: rational thought to be able to not only say this

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Speaker 4: contract is good or bad, but no, this is what

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Speaker 4: we need is how we need to negotiate this contract. Well, now,

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Speaker 4: the value of a lawyers is really nothing because I'm

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Speaker 4: a lawyer, you're a lawyer, Ian's a lawyer.

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Speaker 3: Everybody is a lawyer.

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Speaker 4: If we have the artificial intelligence lawyer, right, So he

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Speaker 4: gave the example as far as going and the dinner

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Speaker 4: and at Thanksgiving, and it's like, now it's like, okay,

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Speaker 4: if I'm gonna have my spouse, the like, okay, I

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Speaker 4: got eight people, sit me at a table right now,

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Speaker 4: It'll just give you a random seating chart. But the

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Speaker 4: new version will think about all scenarios. It will ask

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Speaker 4: you questions, and it will see people accordingly based on

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Speaker 4: their opinion. Stop breaking protocol, man, stop breaking protocol.

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Speaker 2: Say keep going, keep going, keep going, we go down.

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Speaker 4: So that was that was a big, big thing that

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Speaker 4: he really pushed. And he and you could talk about

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Speaker 4: the technical side as far as you're gonna make it

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Speaker 4: it's smarter, and it's it's using more gigs and the

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Speaker 4: whole nine. But for me, those are the two things

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Speaker 4: that really stuck out to me because it was like,

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Speaker 4: everybody's going to have a robot mm hmm. The number

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Speaker 4: one job in the world for men? Put in chat,

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Speaker 4: what's the number one job that was a gym? What's

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Speaker 4: the number one job in the world for men as

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Speaker 4: far as that employs the most men globally? What's the

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Speaker 4: number one job in the world. And Alex you could

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Speaker 4: appreciate this, what's the number one job in the world

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Speaker 4: that employs the most men globally.

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Speaker 3: Let's see if anybody gets.

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Speaker 1: That was one of those like you learn something new

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Speaker 1: every day, which brought me to my point of what

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Speaker 1: I took away and how scary that is.

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Speaker 2: Yeah, I'll chime in, and then you can chime in

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Speaker 2: the mind. Yeah, no, let them do this.

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Speaker 4: The number one job in the world for men is drivers,

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Speaker 4: cab drivers, uber eats truck drivers.

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Speaker 2: Anywhere in the world.

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Speaker 4: You think about it, like, you don't need a skill

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Speaker 4: set to be a driver, you just need a car, right,

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Speaker 4: and you could go to South Africa, you can go

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Speaker 4: to India, there's always a cab driver. There's always like

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Speaker 4: that's the number one job for men globally. Yep, that's

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Speaker 4: going to be a race pretty soon. Yeas driving toamis

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Speaker 4: drives a nothing. They have their partnership with gm Atonomus.

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Speaker 4: Driving is going to take hundreds of millions of jobs.

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Speaker 4: So imagine all of those people. This is the number

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Speaker 4: one employer for men is a driver. And if we

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Speaker 4: don't need a driver because we have a totomist driving,

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Speaker 4: what does that do to all the number one job

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Speaker 4: for men in the world.

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Speaker 1: I think and just to introduct just briefly, the autonomous

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Speaker 1: piece that they displayed was completely different than what we

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Speaker 1: saw like in a tussa where you get in a

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Speaker 1: car and it's kind of scanning your surroundings to make

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Speaker 1: sure that there's a car is not too close to

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Speaker 1: you on your right or your left, or did somebody

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Speaker 1: walk and there's a dog, there's a sidewalk.

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Speaker 2: This was something completely different what we saw.

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Speaker 1: This actually was understanding the physical environment based on any scenario, right,

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Speaker 1: And so it would scan the area and then it

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Speaker 1: would tell you, based on the weather perception, what how

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Speaker 1: you should how it should drive if it snowed, how

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Speaker 1: to drive to a sleep if it was. It studied

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Speaker 1: the weather patterns and so now it's prepared to drive

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Speaker 1: in any condition. Whereas an average human there's going to

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Speaker 1: be human error. This is preparing for the human error

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Speaker 1: before it even happens.

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Speaker 2: Right.

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Speaker 1: So like that piece of understanding the physical world, this

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Speaker 1: is a game, shoed.

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Speaker 2: I'm not sure you finished. Women to want me to

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Speaker 2: go yeah, yeah, So like this is literally in my notes.

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Speaker 1: So, Agent Ki, was that piece you were talking about

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Speaker 1: and I saw some people put in the chat it's

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Speaker 1: that reasoning piece right, so able to ask the question,

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Speaker 1: but it's also able to solve complex problems on its own,

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Speaker 1: which is we're not at that space right now, right,

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Speaker 1: But that is the first thing. The physical AI, like

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Speaker 1: you said, the robotics. I think the piece that he

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Speaker 1: said is that that physical AI with reinforcement learning, and

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Speaker 1: so that's when the machine starts to learn and make

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Speaker 1: decisions in the environment right to maximize the reward. So

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Speaker 1: like this machine is now doing these things and it's like, oh,

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Speaker 1: that's how's supposed to do it, trial and error.

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Speaker 2: This is not supposed to do it. That's how I'm

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Speaker 2: not supposed to do it.

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Speaker 1: It was like when we had we thought of robotics,

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Speaker 1: if they held a ball in their hand and they

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Speaker 1: dropped it, it wasn't like where did the ball go?

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Speaker 1: The ball was just no longer there. The reinforce learning

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Speaker 1: is like, oh, the ball dropped. It must have fell down.

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Speaker 1: I have to now find it, right, So imagine like

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Speaker 1: it's that type of robotics. The interesting thing that he

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Speaker 1: said is like, yes, tbt's are important, right, agents are

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Speaker 1: going to be important. He said, the biggest piece and

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Speaker 1: the biggest opportunity left in the AI puzzle is when

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Speaker 1: physical AI and reinforcement learning are combined, which is when

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Speaker 1: it introduced the robotics that would come inside your home.

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Speaker 1: So we were I mean, we were just sitting there

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Speaker 1: thinking to each other, like wait, hold up, what we're

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Speaker 1: talking about? Big u on over here, and like they're

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Speaker 1: putting robots in people's homes, and they're trying to rent

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Speaker 1: these robots and they already got the price points.

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Speaker 2: So that was the first piece.

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Speaker 1: And then we got to go into the exhibit hall

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Speaker 1: and just like you said, from a technical standpoint, and

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Speaker 1: go watch we so like people talk about blackwell, like

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Speaker 1: we actually saw it like in front of us, right

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Speaker 1: on the table, Like we got to pick and look

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Speaker 1: at it, and.

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Speaker 2: Like we saw what it looked like.

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Speaker 1: And so obviously then the mind starts turning right Like

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Speaker 1: I'm like, there's a few times in life where you

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Speaker 1: feel validated, right, and like the information felt validated, And

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Speaker 1: so I'm asking questions. I'm just trying to pride from engineers,

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Speaker 1: and I'm like, what's that was that? Was that knowing

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Speaker 1: what I'm looking for the answer in mind? And I

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Speaker 1: was like, okay, here all the racks. Who's making these racks? Hey,

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Speaker 1: got my answer. All right, If that's the GPU and

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Speaker 1: this is liquid cooling, who's providing the liquor cooling for this?

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Speaker 2: All right? Bet? If that's the GPU, who's doing the

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Speaker 2: storage for that? Oh?

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Speaker 1: Bet going to vendor markle. You see all the players.

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Speaker 1: All the players are there. So if I'm talking about Micron,

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Speaker 1: Micron is there. If I'm talking about Vertiv in terms

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Speaker 1: of liquor cooling, vertive is there. If we're talking about

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Speaker 1: super Micro, super Micro's there. All these You're starting to

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Speaker 1: see all these players and it's like, oh, this makes sense.

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Speaker 1: And so when we talk about yes, uncertainty is key

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Speaker 1: to how the market moves.

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Speaker 2: AI is still the story.

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Speaker 1: And even when he spoke about deep Seek and he

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Speaker 1: was like, look, you guys got this thing one hundred

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Speaker 1: percent wrong, just because they had it and they found

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Speaker 1: they're still going to need compute and it's still going

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Speaker 1: to take a large amount of money to start to

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Speaker 1: getting these compute these GPUs out, I'm like, damn. Then

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Speaker 1: the last piece was like, how are people going to

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Speaker 1: even compete at this level this? Not only are they saying, hey,

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Speaker 1: here's our product for twenty twenty five, here's our product

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Speaker 1: for twenty twenty six with black Belt Ultra. Here's our

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Speaker 1: product for twenty twenty the second half of twenty twenty

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Speaker 1: six with Ruben, here's our product for twenty twenty seven,

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Speaker 1: Ruben Ultra Yo, here's our product for.

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Speaker 2: Twenty twenty eight, twenty eight Fineman.

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Speaker 1: He's already three years ahead in the products right with

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Speaker 1: people are just trying to make a product to compete for.

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Speaker 4: GPUs that are three times ahead of their nearest competitor.

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Speaker 1: He's three years ahead. I'm talking to the people. I'm

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Speaker 1: like your houses work. They were like, yo, We're in

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Speaker 1: the mindset where the audience is like, hey, it's every year,

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Speaker 1: he said, When we are here, it's every six months.

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Speaker 1: What trunk create new PROCs every six months? On your headtop?

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Speaker 5: An illegal alien from Guatemala charged with raping a child

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Speaker 5: in Massachusetts. An MS thirteen gang member from Al Salvador

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Speaker 5: accused of murdering a Texas man of Venezuelan charged with

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Speaker 5: filming and selling child pornography in Michigan. These are just

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Speaker 5: some of the heinous migrant criminals caught because of President

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Speaker 5: Donald J. Trump's leadership. I'm Christy Noman, the United States

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Speaker 5: Secretary of Homeland Security. Under President Trump, attempted illegal border

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Speaker 5: crossings are at the lowest levels ever recorded, and over

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Speaker 5: one hundred thousand illegal aliens have been arrested. If you

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Speaker 5: are here illegally, your next you will be fine nearly

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Speaker 5: one thousand dollars a day, imprisoned, and deported. You will

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Speaker 5: never return. But if you register using our CBP home

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Speaker 5: app and leave now, you could be allowed to return legally.

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Speaker 5: Do what's right, leave now. Under President Trump, America's laws,

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Speaker 5: border and families will be protected.

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Speaker 2: Sponsored by the United States Department of Homeland Security,